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Uroboros1205

Prismfy MCP Server

by Uroboros1205

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools are clearly distinct: one performs web searches, the other checks quota status. No overlapping functionality or ambiguity in purpose.

    Naming Consistency5/5

    Both tools follow a consistent pattern with the 'prismfy_' prefix and lowercase_snake_case. Names clearly indicate action (search) and resource (quota), maintaining uniformity.

    Tool Count3/5

    With only two tools, the server feels thin for a search service, but it covers the essential operations (search and quota). This aligns with the borderline range where tools are minimal yet purposeful.

    Completeness4/5

    The core search and quota tracking are covered, but advanced features like pagination, result filtering, or search history are absent. These are minor gaps that agents can work around for basic use cases.

  • Average 3.5/5 across 2 of 2 tools scored. Lowest: 2.4/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 1 commit in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden for behavioral disclosure. It only states the return fields and does not disclose side effects, rate limits, read-only nature, pagination, or any other behavioral traits. An agent cannot tell whether this is a stateless query or if it has implications for quotas or costs. The minimal mention of 'request metadata' hints at some response detail but is not substantive.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness3/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single short sentence with no filler, so it is concise. However, it is under-specified, missing crucial information about parameters, usage, and behavior. It front-loads the core action but sacrifices necessary detail. It is neither verbose nor well-structured enough to be considered appropriately sized.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a tool with six parameters, no output schema, and no annotations, the description is incomplete. It provides only the high-level purpose and a list of return fields, omitting any guidance on parameter semantics, usage constraints, or edge cases. An agent would struggle to craft a correct request without additional information, especially for parameters like 'engines' or 'timeRange'.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters1/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, so the schema provides no semantic meaning for parameters. The description does not explain any of the six parameters (query, page, domain, engines, language, timeRange). It does not hint at what 'engines' might be, what formats or values are expected for 'timeRange', or how 'page' pagination works. The description fails to compensate for the missing parameter documentation, leaving the agent to guess.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description states a specific verb ('Search') and resource ('the web through Prismfy'), and explicitly enumerates what it returns (titles, URLs, snippets, source engines, request metadata). This distinguishes it from the sibling prismfy_quota, which is clearly about quota management. It could be slightly more explicit about the tool's role relative to other search options, but it is unambiguous.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description gives no guidance on when to use this tool versus alternatives. It does not mention the sibling prismfy_quota, nor does it specify any prerequisites, limitations, or contexts where a different tool would be preferred. The agent must infer the appropriate use case solely from the name and generic phrase 'Search the web.'

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries the full behavioral burden. The verb 'Get' clearly signals a read-only operation with no side effects. The description also explicitly enumerates the fields returned, providing sufficient transparency for an agent to understand the tool's behavior.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, compact sentence that front-loads the verb and resource, then lists the concrete data points. Every word earns its place, and there is no redundant or vague phrasing.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    The tool has no output schema, so the description must explain the return values. It does so explicitly, naming each piece of returned information (tier, used searches, remaining searches, reset date). An agent has everything needed to call the tool and interpret its result.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    With zero parameters, the schema is trivially complete and the description correctly adds no parameter information. Since there is nothing to explain, the baseline of 4 applies; the description does not need to compensate for any missing schema details.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description uses a specific verb ('Get') and a clear resource (current Prismfy tier, used/remaining searches, reset date). It is unambiguous and distinguishes itself from the only sibling (prismfy_search) by focusing on quota rather than search functionality.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description clearly implies when to use the tool: whenever an agent needs quota information for Prismfy. It does not explicitly exclude alternatives, but with only one sibling and a distinct purpose, the usage context is clear enough without explicit 'when-not-to-use' guidance.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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  • Evaluate tool definition quality.

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